Statistical Modelling of Information Sharing: Community, Membership and Content
W.-Y. Ng, W.K. Lin, D.M. Chiu

TL;DR
This paper presents a statistical model of online information sharing communities, analyzing how membership dynamics and content availability influence community growth, stability, and critical thresholds for sustainability.
Contribution
It introduces a simple yet insightful model capturing the coupled dynamics of membership and content, revealing critical thresholds and multiple equilibria in community growth.
Findings
Identifies a sharp growth threshold for community sustainability.
Shows the existence of multiple equilibria in community dynamics.
Highlights the importance of content matching and search efficiency.
Abstract
File-sharing systems, like many online and traditional information sharing communities (e.g. newsgroups, BBS, forums, interest clubs), are dynamical systems in nature. As peers get in and out of the system, the information content made available by the prevailing membership varies continually in amount as well as composition, which in turn affects all peers' join/leave decisions. As a result, the dynamics of membership and information content are strongly coupled, suggesting interesting issues about growth, sustenance and stability. In this paper, we propose to study such communities with a simple statistical model of an information sharing club. Carrying their private payloads of information goods as potential supply to the club, peers join or leave on the basis of whether the information they demand is currently available. Information goods are chunked and typed, as in a file…
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Taxonomy
TopicsCaching and Content Delivery · Peer-to-Peer Network Technologies · Recommender Systems and Techniques
